ChillSemesterSign in

RM 742: Data Sci via Machine Learning at Queens College

4 credits · Spring 2027

Data Sci via Machine Learning (RM 742) at Queens College has 1 way to take it in Spring 2027. 1 of 1 section has an open seat right now.

The professor is: Elliot Gangaram / Bryan Nevarez.

Compare them below, check the days and times, and add the course to your schedule.

Requirements

Prerequisites: MATH 241, MATH 231, CSCI 111 (or equivalent)

About this course

Philosophy of modeling and learning using data. Prediction using linear, polynomial, interaction regressions and machine learning including neural nets and random forests. Probability estimation with asymmetric cost classification. Underfitting vs. overfitting and R-squared. Model validation. Correlation vs. causation. Interpretations of linear model coefficients. Formal instruction of statistical computing. Data manipulation and visualization using modern libraries. Writing Intensive. Recommended corequisites include ECON 382, MATH 341, MATH 369 or their equivalents.

Professors for RM 742 at Queens, Spring 2027

Ordered chillest first. A Chill Rank compares a professor with other CUNY professors on Rate My Professors difficulty, rating and would-take-again; it needs at least 3 ratings. How it works

RM 742 sections, times and seats

Seat status as of Oct 5, 12:36 AM ET. Seats can change between refreshes. How fresh is this?

001-LEC Regular
Mon/Wed · 3:45 PM - 5:35 PM
Mon/Wed · 3:10 PM - 3:40 PM
Mon · 5:40 PM - 7:30 PM
Kiely Hall 324
Elliot Gangaram / Bryan NevarezNo Rate My Professors rating found
In PersonOpen

Questions about RM 742 at Queens

Who teaches RM 742 at Queens in Spring 2027?
Elliot Gangaram / Bryan Nevarez is listed for Spring 2027. Each name links to a page with their Chill Rank and Rate My Professors numbers.
Is RM 742 at Queens hard?
We do not have enough Rate My Professors ratings for the professors teaching RM 742 yet to say. The Chill Rank appears once a professor has at least 3 ratings.
What if a RM 742 section is full?
Try another section, join the waitlist in CUNYfirst if there is one, or ask the department. You can also watch a full section and get an email when a seat opens; you still enroll yourself in CUNYfirst.